PrePhyloPro

Online prediction of whole proteome linkages based on phylogenetic profiles

Current Version 1.0.1 (December 5, 2017)

What is PrePhyloPro?

PrePhyloPro is an online tool for whole proteome linkages prediction. The predicted linkages reveal the direct or indirect connections. It can be used to detect novel physical protein-protein interactions, new components of biological complexes, and potential linkages in signaling pathways or metabolic processes. The internal algorithm is based on phylogenetic profiles which show genes occurence (presence or absence) in different species.

High accuracy

Higher accuracy compared with single co-occurrency (Jaccard similarity, Pearson correlation coefficient, and mutual information) and module-based methods.

Easy-to-use

Only a data table in the txt or csv format is all you need to prepare. Additional webpage entering parameters are supported for advanced usage.

High quality figures

Outputs are user-friendly visualized online and could be easily downloaded and restored on local computers. High quality figures and formatted tables are provided for academic publication.

Extensive datasets

Profiles were construced from 972 different species containing 276 eukaryotic, 614 bacterial, and 82 archaea species, and mitochondrial and chloroplast proteins were also included.

open source

Free and open source to all academic users. Internal data including phylogenetic profiles and gene annotation are downloadable. The prediction algorithm is open and hosted in GitHub.

More...

D3-based interactive network visualization. Pathway analysis of predicted partners will be further supported. More organisms will be supported.

New features

Examples

Human F1Fo-ATP synthase predicted linkages, ATP5E Circos plot

Click to see the example: Example


Click to download example input files:  

Citation:

Niu Y, Moghimyfiroozabad S, Safaie S, Yang Y, Jonas EA, Alavian KN (2017) Phylogenetic Profiling of Mitochondrial Proteins and Integration Analysis of Bacterial Transcription Units Suggest Evolution of F1Fo ATP Synthase from Multiple Modules. J Mol Evol 85: 219 https://doi.org/10.1007/s00239-017-9819-3

Human F1Fo-ATP synthase predicted linkages, F1 Circos plot

Click to see the example: Example


Click to download example input files:  

Citation:

Niu Y, Moghimyfiroozabad S, Safaie S, Yang Y, Jonas EA, Alavian KN (2017) Phylogenetic Profiling of Mitochondrial Proteins and Integration Analysis of Bacterial Transcription Units Suggest Evolution of F1Fo ATP Synthase from Multiple Modules. J Mol Evol 85: 219 https://doi.org/10.1007/s00239-017-9819-3

Arabidopsis F1Fo-ATP synthase predicted linkages, ATP5 Circos plot

Click to see the example: Example


Click to download example input files:  

Citation:

Niu Y, Moghimyfiroozabad S, Safaie S, Yang Y, Jonas EA, Alavian KN (2017) Phylogenetic Profiling of Mitochondrial Proteins and Integration Analysis of Bacterial Transcription Units Suggest Evolution of F1Fo ATP Synthase from Multiple Modules. J Mol Evol 85: 219 https://doi.org/10.1007/s00239-017-9819-3

Only one input candicate genes

Click to download example input files:  

You are encouraged to share your own examples, we will be very happy to show them on this site. If you are interested, please compress the result files along with the citation information (PubMed ID, article links, or any other messages), and emails us. Thanks!

Get Started

Step 1

Algorithm parameters

1 ≤
≤ 500

Step 2

Plot parameters

0 <
0 <

Step 3

Candidate gene list

Full Documentation

More details about setting paramters, file formats, and source codes are hosted on GitHub.

More on GitHub

Contact

I hope you find PrePhyloPro useful. Feel free to get in touch if you have any questions or suggestions.

If any unexpected results return (like an error webpage), please compress your input files and email us.


Citation:

Niu Y, Liu C, Moghimyfiroozabad S, Yang Y, Alavian KN. (2017) PrePhyloPro: phylogenetic profile-based prediction of whole proteome linkages. PeerJ 5:e3712 https://doi.org/10.7717/peerj.3712

Yulong Niu

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